JP6544291B2 - Method and apparatus for diagnosing abnormality of joint drive robot - Google Patents

Description

  The present invention relates to an abnormality diagnosis method and an abnormality diagnosis apparatus for a joint drive robot, and more particularly to an abnormality diagnosis method and an abnormality diagnosis apparatus for a joint drive robot for diagnosing an abnormality in a joint drive robot.

  By using a robot (robot arm) such as an industrial robot, predetermined work such as welding is performed at a manufacturing site such as a car body. The robot operates at a desired position by executing an operation program (teaching data) programmed by robot teaching (teaching), for example.

  The robot is controlled such that an end effector provided at the tip of the robot moves to a desired position by driving each joint by a drive source such as a motor. The power of the motor is transmitted to each joint of the robot via a reduction gear. In such a robot, there is a possibility that the robot may become inoperable due to the occurrence of an abnormality in the robot due to the deterioration of the motor or the reduction gear. Therefore, it is desirable to diagnose robot anomalies before they become inoperable.

  In relation to the above-mentioned technology, Patent Document 1 discloses a robot degradation diagnostic device. The robot deterioration diagnosis device according to Patent Document 1 is characterized by a group of characteristic data as data used for deterioration diagnosis (cycle time, deceleration provided by each joint axis) every time one cycle regeneration operation is completed in a work program used for deterioration diagnosis. Machine life, average torque of motor, maximum torque, average rotation speed, maximum rotation speed, etc. are recorded in memory. And the robot degradation diagnostic device concerning patent document 1 analyzes this characteristic data group by a statistical method, and diagnoses the mechanical degradation symptom of a robot arm based on an analysis result. With such a configuration, the robot degradation diagnostic device according to Patent Document 1 detects the presence or absence of degradation of the robot drive system even when there is a difference in the characteristic data between when the regeneration operation was performed in the past and when the regeneration operation was currently performed. It can be judged.

JP 2005-148873 A

  In the method according to Patent Document 1, the deterioration symptom is diagnosed using the characteristic data generated when the one-cycle regeneration operation in the work program is completed. That is, in the method according to Patent Document 1, the characteristic data of one cycle in the work program is used. Here, in the case where characteristic data of one cycle in the working program is simply used, if one cycle in the working program does not include a process for making the robot abnormal appear, the robot abnormality is detected and scattered. There is a fear. That is, if a process that makes the robot abnormal appear is not included, even if the robot is abnormal, the characteristic data such as the cycle time may not show abnormality (deterioration).

  The present invention provides an abnormality diagnosis method and an abnormality diagnosis apparatus for a joint drive robot capable of detecting a robot abnormality more reliably.

  The abnormality diagnosis method for a joint drive robot according to the present invention is an abnormality diagnosis method for diagnosing an abnormality in a joint drive robot that operates by driving a joint, wherein the robot has predetermined target positions and required accuracy. A process controlled by an operation program configured of a plurality of associated processes, and among the plurality of processes, the process whose requirement accuracy is higher than a predetermined value is set as a process to be diagnosed, and the operation program To control the difference between the position of the control target of the robot and the target position in the diagnosis target process to fall within the allowable range of the required accuracy, and the measurement value and the measurement for the diagnosis target process An abnormality diagnosis of the robot is performed using a reference value regarding the value.

  The abnormality diagnosis apparatus for a joint drive robot according to the present invention is an abnormality diagnosis apparatus for diagnosing an abnormality in a joint drive robot that operates by driving a joint, wherein the robot has predetermined target positions and required accuracy. Setting means configured to set the process of which the required accuracy is higher than a predetermined value among the plurality of processes as a process to be diagnosed, which is controlled by an operation program configured of a plurality of associated processes; The process to be diagnosed when control is performed using the operation program such that the difference between the position of the control target of the robot and the target position falls within the allowable range for the required accuracy in the process to be diagnosed And diagnostic means for diagnosing an abnormality of the robot using a measured value of and a reference value related to the measured value.

  In a process with high required accuracy, it is difficult to control the robot so that the difference between the position of the controlled object of the robot and the target position falls within the allowable range. And the tendency is more remarkable as the robot in which the abnormality is occurring. That is, by performing control in a process with high required accuracy, it is possible to make the robot abnormal. In other words, measured values in a process with high required accuracy are likely to differ between when an abnormality occurs in the robot and when no abnormality occurs. Therefore, according to the present invention, it is possible to detect the robot's abnormality more reliably by performing the abnormality diagnosis using the measured value and the reference value in the process with high required accuracy.

In addition, preferably, the working time required for at least one process including the diagnosis target process is measured, and a difference between the measured working time and the reference value of the working time is used to diagnose the abnormality of the robot. .
The working time may increase as the degree of robot abnormality increases. Therefore, by performing the abnormality diagnosis using the working time, it is possible to more surely detect the abnormality of the robot.

In addition, preferably, a time from the end of the process before the process to be diagnosed to the end of the process to be diagnosed is measured as the work time.
By this configuration, it is possible to eliminate the influence of other devices and the like on the measured operation time. Therefore, it is possible to detect the robot abnormality more reliably.

  According to the present invention, it is possible to provide an abnormality diagnosis method and an abnormality diagnosis apparatus for a joint drive robot capable of detecting a robot abnormality more reliably.

FIG. 1 is a diagram showing a robot control system according to a first embodiment. FIG. 2 is a functional block diagram showing a configuration of a control device according to Embodiment 1. FIG. 6 is a diagram exemplifying an operation program stored by an operation program storage unit according to the first embodiment. FIG. 6 is a diagram showing the contents managed by the measurement value management unit according to the first embodiment. It is a figure which shows the state from which the operation | movement of a robot transfers to a diagnostic object process from the process before a diagnostic object process. It is a figure for demonstrating control operation of a robot. It is a figure for demonstrating the difference in the cycle time in the time of the normal time of a robot, and abnormality. 5 is a flowchart showing an abnormality diagnosis method performed by the control device according to the first embodiment. It is a flowchart which shows the robot control processing in the flowchart shown in FIG. It is a flowchart which shows the abnormality-diagnosis process in the flowchart shown in FIG.

Embodiment 1
Hereinafter, embodiments of the present invention will be described with reference to the drawings.
FIG. 1 is a diagram showing a robot control system 1 according to a first embodiment. The robot control system 1 includes a robot 10 and a control device 100. The control device 100 controls the operation of the robot 10 using an operation program to control the robot 10 to a desired position. The control device 100 also has a function as an abnormality diagnosis device that diagnoses an abnormality of the robot 10. Details will be described later.

  The robot 10 is installed in the vicinity of a production line of a vehicle. The robot 10 is, for example, a robot for performing predetermined work such as welding (for example, spot welding) on a vehicle. For example, at the time of manufacturing a vehicle, the robot 10 performs welding or the like using a welding gun or the like provided on the end effector 12. The robot 10 also has one or more joints 14, a motor (not shown) that drives the joints 14, and a reduction gear (not shown) that transmits the power of the motors to the joints 14. The robot 10 controls a motor by the control device 100 to perform a desired operation. That is, the robot 10 is a joint drive robot that operates by driving the joint 14. Then, the control device 100 controls the robot 10 so that the position of the distal end portion 12a of the end effector 12 becomes a desired position (target position) in each process in the operation program. That is, in the present embodiment, the control target of the robot 10 is the tip 12a.

  The control device 100 has, for example, a function as a computer. The control device 100 may be mounted inside the robot 10 or may be communicably connected to the robot 10 via a wired or wireless connection. The control device 100 includes a central processing unit (CPU) 101, a read only memory (ROM) 102, a random access memory (RAM) 103, an input / output (I / O) 104, and a user interface (UI) 105.

  The CPU 101 has a function as a processing device that performs control processing, arithmetic processing, and the like. The ROM 102 has a function for storing a control program executed by the CPU 101, an arithmetic program, and the like. The RAM 103 has a function for temporarily storing processing data and the like. The I / O 104 is an input / output device, receives data and signals from the outside, and outputs data and signals to the outside. The UI 105 includes, for example, an input device such as a keyboard and an output device such as a display. The UI 105 may be configured as a touch panel in which an input device and an output device are integrated. Here, the ROM 102 is configured to be able to store an operation program (teaching data) for controlling the robot 10.

  Here, in the present embodiment, the actual position of the control target of the robot 10 is not controlled to exactly match the target position by the control of the control device 100. There may be a certain degree of deviation between the actual position of the control target of the robot 10 and the target position, depending on the required accuracy previously determined in each process of the operation program. That is, the control device 100 can control the position of the control target of the robot 10 to the target position in the process if the actual position converges (reaches) within the allowable range corresponding to the required accuracy based on the target position. The control of the next process is performed by terminating the control in that process. That is, in each process, control device 100 controls robot 10 so that the difference (deviation) between the position of the control target (tip portion 12 a) of robot 10 and the target position falls within the allowable range corresponding to the required accuracy. Do.

  If the required accuracy is high, the corresponding allowable range is small, and if the required accuracy is low, the corresponding allowable range is large. By performing such control, the actual position can be quickly converged within the allowable range in the process where the required accuracy is low, so that the working time can be shortened.

  FIG. 2 is a functional block diagram showing the configuration of the control device 100 according to the first embodiment. The control device 100 includes an operation program storage unit 112, a diagnosis target process setting unit 114, a robot control unit 116, an actual position acquisition unit 118, a working time measurement unit 120, a measured value management unit 122, an abnormality diagnosis unit 124, and a warning output unit. Having 126. Each component of control device 100 shown in FIG. 2 can be realized by CPU 101 executing a program stored in ROM 102. In addition, necessary programs may be recorded in any non-volatile recording medium, and the programs may be installed as needed. Each component shown in FIG. 2 is not limited to being realized by software as described above, but may be realized by hardware such as some circuit element.

  Also, one or more of the components shown in FIG. 2 may be realized by a device separate from the control device 100. For example, the diagnosis target process setting unit 114, the working time measurement unit 120, the measurement value management unit 122, the abnormality diagnosis unit 124, and the warning output unit 126 may be realized by an abnormality diagnosis device different from the control device 100. That is, the device that controls the robot 10 and the device that diagnoses an abnormality of the robot 10 may be physically separate devices. In this case, the abnormality diagnosis device can have the same configuration as the hardware configuration of the control device 100 shown in FIG.

The operation program storage unit 112 stores an operation program for operating the robot 10.
FIG. 3 is a diagram illustrating an operation program 200 stored by the operation program storage unit 112 according to the first embodiment. The operation program 200 is configured by a plurality of steps “1” to “M” (M is an integer of 2 or more). In each process, the operation speed of the robot in the process, the required accuracy in the process, the target position in the process, the presence or absence of setting of the diagnosis target (diagnosis target setting), and the I / O signal are associated.

  The motion speed of the robot is faster as the number is larger. In the example of FIG. 3, the fastest speed "9" is set in all steps. The required accuracy indicates how close the position of the control target of the robot 10 should be to the target position. As the required accuracy is higher, in the process, it is necessary to control the position of the control target of the robot 10 closer to the target position. Here, the required accuracy is higher as the number is smaller. In the example of FIG. 3, the required accuracy is provided from the highest accuracy “0” to the lowest accuracy “4”. For example, in the process “1”, control is performed with an accuracy “1”, and in the process “2”, control is performed with an accuracy “2”. Further, in the process "N" (N is an integer of 1 or more and M or less), control is performed with the highest accuracy "0". Further, in the process "N-1" immediately before the process "N", the control is performed with the accuracy "2".

  The target positions Pt (Pt_1 to Pt_3,..., Pt_N-1 to Pt_N,... Pt_M) indicate desired positions of the tip 12a of the end effector 12 in the corresponding process. Here, the target position may indicate position coordinates (x, y, z) on the three-dimensional space of the tip 12a to be controlled. Furthermore, the target position may indicate the joint angle (target joint angle) of each joint 14 such that the tip 12a reaches the target position. The control device 100 can control the distal end 12a of the robot 10 to a target position by controlling each joint 14 to a target joint angle.

  The diagnosis target setting indicates whether the process is a target of abnormality diagnosis of the robot 10 or not. The process in which the diagnosis target setting is set to "present" is the process to be diagnosed, that is, the process to be diagnosed. The abnormality diagnosis unit 124 diagnoses the abnormality of the robot 10 using the measurement value measured for the process (diagnosis target process) in which the diagnosis target setting is set to "present". Details will be described later.

  The “I / O signal” indicates a signal transmitted / received when the control device 100 (or the robot 10) communicates with another device (a device other than the control device 100 and the robot 10) in each process. If any signal is set in “I / O signal”, in the process, the robot 10 cooperates with another device (or worker) or cooperates with another device (or worker) To work. On the other hand, in the process in which nothing is set in the "I / O signal", communication with other devices is not performed. In other words, in the process, the robot 10 to be diagnosed operates alone.

  The “interlock signal” set in the process “2” is, for example, a signal for stopping the operation of the robot 10 until another device (or operator) performs some operation to end the operation. . The “welding machine communication” set in the process “3” indicates a signal input / output to cause the welding machine attached to the end effector 12 to perform welding. The “completion signal” set in the process “M” is a signal for notifying another apparatus that all the processes of the operation program 200 have been completed.

  The diagnosis target process setting unit 114 (setting unit) sets at least one of the plurality of processes of the operation program 200 as a diagnosis target process. Here, the diagnosis target process setting unit 114 sets a process whose request accuracy is higher than a predetermined value as a diagnosis target process. Here, the “predetermined value” is, for example, the accuracy “1”. Therefore, a process in which the required accuracy is higher than a predetermined value is a process in which the accuracy is "0". In the example of FIG. 3, the required accuracy of the process “N” is the highest accuracy “0”. Therefore, the diagnosis target process setting unit 114 sets the process “N” as a diagnosis target process.

  The robot control unit 116 controls the robot 10 in accordance with the operation program 200. Specifically, the robot control unit 116 transmits a control signal to the robot 10 so as to control the position of the tip 12a to the target position in each process. For example, the control signal may be a target joint angle of each joint 14. A motor driving each joint 14 adjusts the joint angle of each joint 14 according to the control signal. Details will be described later. Also, the robot control unit 116 may perform feedback control using the actual position of the tip 12 a of the robot 10 acquired by the actual position acquisition unit 118 described later.

  Here, "the robot control unit 116 controls the position of the tip 12a to the target position", but as described above, the robot control unit 116 strictly matches the position of the tip 12a to the target position. It does not mean to control to do. The robot control unit 116 controls the robot 10 so that the actual position of the tip 12 a reaches the tolerance range corresponding to the required accuracy in each process. That is, in each process, the robot control unit 116 performs control so that the difference between the position of the tip 12 a of the robot 10 and the target position falls within the allowable range of the required accuracy. Therefore, the robot control unit 116 controls the robot 10 so that the actual position of the tip 12a approaches the target position as the process with high required accuracy.

  The actual position acquisition unit 118 acquires the actual position of the tip 12 a according to a signal from the robot 10. For example, when a sensor that measures the position of the tip 12a is provided, the actual position acquisition unit 118 may receive a signal from that sensor. When each joint 14 is provided with an encoder for measuring the actual joint angle of the joint 14, the actual position acquisition unit 118 receives a signal from the encoder and determines the position of the tip 12a from the received signal. May be calculated. The actual position acquisition unit 118 may output information indicating the acquired actual position to the robot control unit 116 for feedback control before each process of the robot 10 is completed. On the other hand, when each step of the robot 10 is completed, the actual position acquisition unit 118 outputs, to the measurement value management unit 122, information indicating the position (attainment position) at which the tip 12a has reached.

  The working time measurement unit 120 (measuring means) measures working time (cycle time) for the process to be diagnosed and the set process. Specifically, the working time measurement unit 120 measures the cycle time including the process to be diagnosed. More specifically, the working time measurement unit 120 measures the time from the end of the process immediately before the diagnosis target process to the end of the diagnosis target process as a cycle time (process cycle time). Details will be described later. The working time measurement unit 120 outputs information indicating the measured process cycle time to the measurement value management unit 122.

  The measurement value management unit 122 manages the measurement values measured in accordance with the operation of the robot 10 in the diagnosis target process. Specifically, the measurement value management unit 122 manages the process cycle time and the value regarding the position of the tip 12a. Hereinafter, description will be made using the drawings.

  FIG. 4 is a diagram showing the contents managed by the measurement value management unit 122 according to the first embodiment. The measurement value management unit 122 manages the process cycle time, the arrival position, the target position, and the arrival deviation amount, which are measurement values, for the process “N” which is a process to be diagnosed. Further, the measurement value management unit 122 manages the process cycle time, the arrival position, the target position, and the arrival deviation amount, which are reference values for abnormality diagnosis, for the process “N” which is a process to be diagnosed. Here, the “reference value” is a value when the robot 10 is normal (ideally, there is no deterioration). Further, the “attainment deviation amount” indicates the deviation amount between the arrival position at the time when control in the process is completed and the target position.

  As shown in FIG. 4, Ts represents a reference value of process cycle time in process “N”, and T represents a measured value of process cycle time. Also, Pt_N indicates the target position of the tip 12 a of the robot 10 in the process “N”, and P indicates the reached position of the tip 12 a of the robot 10. At this time, in the ideal state in which the robot 10 is completely normal, the tip 12a of the robot 10 can reach the target position. Therefore, the arrival deviation amount at this time is zero. On the other hand, as the robot 10 is used, it becomes difficult to control the tip 12a of the robot 10 so as to completely match the target position due to the deterioration of the speed reducer of the robot 10 or the like. Therefore, at the time of measurement, there is a nonzero arrival deviation amount ΔP between the target position Pt_N and the arrival position P. The reaching deviation amount ΔP is within the allowable range regarding the required accuracy in the process “N”.

  The abnormality diagnosis unit 124 (diagnosis means) performs abnormality diagnosis of the robot 10 using the measurement value and the reference value for the process to be diagnosed. Specifically, the abnormality diagnosis unit 124 performs abnormality diagnosis of the robot 10 according to the cycle time of the process to be diagnosed. Details will be described later. If the abnormality diagnosis unit 124 determines that an abnormality occurs in the robot 10, the abnormality diagnosis unit 124 outputs a command to the warning output unit 126 to output a warning.

  The warning output unit 126 outputs a warning indicating that an abnormality has occurred in the robot 10 according to the abnormality diagnosis by the abnormality diagnosis unit 124. The warning output unit 126 may output different warnings according to the degree of abnormality of the robot 10. The warning may be visually detectable such as a lamp, or may be audiblely detectable such as an alarm sound.

Next, the mechanism of the abnormality diagnosis according to the first embodiment will be described.
FIG. 5 is a diagram showing a state in which the operation of the robot 10 transitions from the process before the process to be diagnosed to the process to be diagnosed. FIG. 5 exemplifies a state in which the process transitions from the process “N-1” to the process “N” which is a process to be diagnosed. In the process “N−1”, the robot 10 is controlled to the position (posture) as illustrated in (A), and in the process “N”, the robot 10 is as illustrated in (B) Control). At this time, when the process transitions from the process “N−1” to the process “N”, the position of the distal end portion 12 a of the robot 10 moves from the arrival position P_N−1 to the arrival position P_N as shown by arrow A. Here, the reached position P_N-1 is within the allowable range in the process "N-1" based on the target position Pt_N-1. That is, the difference between the reached position P_N-1 and the target position Pt_N-1 is within the allowable range in the process "N-1". Similarly, the reached position P_N is within the allowable range in the process “N” based on the target position Pt_N. That is, the difference between the reached position P_N and the target position Pt_N is within the allowable range in the process “N”.

  Here, the difference between the arrival position P_N and the target position Pt_N (the arrival deviation amount ΔP) may be, for example, the distance between the arrival position P_N and the target position Pt_N. In this case, the “acceptable range” may be an allowable maximum value of the distance between the arrival position P_N and the target position Pt_N. Further, the required accuracy in the process “N−1” is “2”, and the required accuracy in the process “N” is “0”. Therefore, as shown in FIG. 5, the tolerance in the process “N” is smaller than the tolerance in the process “N−1”. Therefore, it is more difficult for the process “N” to allow the position of the tip 12 a of the robot 10 to reach the allowable range than the process “N−1”.

  FIG. 6 is a diagram for explaining the control operation of the robot 10. The robot control unit 116 performs control in stages for each robot control cycle Δt in the process of controlling the tip 12 a of the robot 10 from the position of the process “N−1” to the position of the process “N”. That is, the robot control unit 116 does not set the command value to the target position Pt_N at one time in the process of transitioning from the process “N−1” to the process “N”, but different command values for each robot control cycle Δt. Control in stages. As the robot control period Δt progresses, the command value approaches the target position Pt_N. Here, the robot control cycle Δt is a cycle for controlling the robot 10, and may be determined according to the performance of the CPU 101 of the control device 100. The command value for each robot control cycle Δt may be included in the operation program.

  Here, the robot 10 whose use period has advanced tends to be uncontrollable according to the command value due to an increase in load resistance caused by deterioration of the speed reducer and the like. Therefore, when the robot 10 moves during the robot control cycle Δt, a deviation Δp occurs between the command value pt and the actual value p at time t + Δt. The deviation Δp tends to increase as the deterioration of the robot 10 progresses.

  FIG. 7 is a diagram for explaining the difference in cycle time between when the robot 10 is normal and when it is abnormal. FIG. 7 illustrates a state in which the process transitions from the process “N−1” to the process “N”. A point in time when the tip end 12a of the robot 10 moves to the arrival position P_N-1 in the process "N-1" and the control in the process "N-1" is finished is taken as time t.

  In a normal state, the tip 12a moves to the position p1 at time t + Δt, moves to the position p2 at time t + 2Δt, and moves to the position p3 at time t + 3Δt. At the third robot control cycle Δt, the tip 12 a reaches the position P_N which is within the allowable range of the process “N”. Therefore, the process cycle time of process "N" at normal time is 3Δt.

  On the other hand, in the abnormal state, the tip 12a moves to the position p1 'at time t + Δt, but a deviation occurs between the position p1' and the position p1. Next, the distal end portion 12a moves to the position p2 'at time t + 2Δt, but there is a deviation between the position p2' and the position p2. Next, the distal end portion 12a moves to the position p3 'at time t + 3Δt, but a deviation occurs between the position p3' and the position p3.

  Here, at the third robot control cycle Δt, the tip 12a has not yet reached within the allowable range of the process "N". Therefore, the robot control unit 116 controls the robot 10 so that the tip end 12a reaches the allowable range at the next robot control cycle Δt. Then, at time t + 4Δt, it moves to the position p4 '. At the fourth robot control cycle Δt, the tip 12 a reaches a position P_N that is within the allowable range of the process “N”. Therefore, the process cycle time of process “N” at the time of abnormality is 4Δt.

  As described above, since the required accuracy of the process “N” is the maximum “0”, the allowable range is very small. Therefore, it is not easy for the robot control unit 116 to bring the position of the tip 12a within the allowable range. And it is not easy to perform control so that the robot control unit 116 causes the position of the distal end portion 12a to reach the allowable range as the robot 10 in which the abnormality is occurring is increased load resistance or the like, and the distal end portion It takes a long time for the position of 12a to reach the allowable range. That is, the process cycle time for the process “N” by the robot 10 in which the abnormality has occurred is longer than the process cycle time for the process “N” by the normal robot 10. The control apparatus 100 according to the first embodiment performs abnormality diagnosis using such an increase in process cycle time at the time of abnormality. That is, in the first embodiment, the process cycle time is measured as a physical quantity for the process to be diagnosed. Then, the control device 100 according to the first embodiment performs abnormality diagnosis of the robot 10 using the difference between the measured process cycle time and the reference value of the process cycle time (process cycle time at normal time).

  Note that in a process in which the required accuracy is not very high, the allowable range is not so small, so that the robot control unit 116 causes the position of the tip 12a to reach the allowable range even if the robot 10 has an abnormality. Not so difficult. Therefore, in such a process, a difference in process cycle time hardly occurs between an abnormal time and a normal time. That is, in such a process, there is a possibility that the abnormality does not appear. In this case, it is possible that the process cycle time can not be used to detect an abnormality. On the other hand, since the control apparatus 100 according to the first embodiment measures the cycle time in the process with high required accuracy and performs the abnormality diagnosis, when an abnormality occurs in the robot 10, the process cycle time is shorter than that in the normal case. It is likely to grow. That is, in a process with high required accuracy, an abnormality is easily manifested. Therefore, the control device 100 according to the first embodiment can detect abnormality of the robot 10 more reliably.

  That is, the measurement value (cycle time) in the step with high required accuracy is more likely to indicate an abnormality when an abnormality occurs in the robot 10 than the measurement value in the step with low required accuracy. In other words, in the process where the required accuracy is high, the measurement value (cycle time) is likely to be different between when an abnormality occurs in the robot 10 and when no abnormality occurs. Therefore, the control apparatus 100 according to the first embodiment can detect abnormality of the robot 10 more reliably by performing abnormality diagnosis using the measurement value and the reference value in the process with high request accuracy.

  FIG. 8 is a flowchart showing an abnormality diagnosis method performed by the control device 100 according to the first embodiment. The operation program storage unit 112 of the control device 100 stores an operation program (step S102). The diagnosis target process setting unit 114 of the control device 100 sets the process “N” whose request accuracy is higher than the predetermined threshold Th1 among the plurality of processes of the operation program as the diagnosis process (step S104). .

  Next, the robot control unit 116 of the control device 100 controls the robot 10 according to the operation program (step S110). The process of S110 will be described in detail with reference to FIG. Next, the control device 100 diagnoses an abnormality based on the measured value obtained by measuring the physical quantity of the process to be diagnosed for the process "N" which is the process to be diagnosed (step S20). The process of S20 will be described in detail with reference to FIG.

  FIG. 9 is a flowchart showing the robot control process (S110) in the flowchart shown in FIG. First, the robot control unit 116 initializes the process “K” to be controlled, that is, K = 1 (step S112). Next, the robot control unit 116 controls the robot 10 so that the position of the tip 12a of the robot 10 approaches the target position Pt_K of the process “K” by starting the operation of the process “K” (step S114) (Step S116).

  The robot control unit 116 determines whether the actual position P of the distal end 12a has converged within the allowable range of the process "K" (step S118). Specifically, the robot control unit 116 determines whether the difference between the actual position P and the target position Pt_K is within the allowable range of the process “K”. Then, if it is determined that the actual position P of the distal end portion 12a does not converge within the allowable range of the process "K" (NO in S118), the process returns to S116. On the other hand, when it is determined that the actual position P of the tip 12a converges within the allowable range of the process "K" (YES in S118), the robot control unit 116 ends the control in the process "K" ( Step S120).

  Next, the robot control unit 116 determines whether the last step in the operation program is completed, that is, whether K = M (step S122). If it is determined that the last step is not completed (NO in S122), the robot control unit 116 increments K by one (Step S124), and repeats the processing of S114 to S122 for the next step. On the other hand, when it is determined that the last process is completed, that is, K = M (YES in S122), the robot control unit 116 ends the control of the robot 10 in the operation program (step S126).

FIG. 10 is a flowchart showing the abnormality diagnosis processing (S20) in the flowchart shown in FIG. First, the working time measuring unit 120 of the control device 100 determines the process cycle time from the end of the process “N-1” immediately before the process “N” which is the process to be diagnosed to the end of the process “N”. T is measured (step S202). Next, the abnormality diagnosis unit 124 of the control device 100 acquires the process cycle time Ts serving as a reference from the measurement value management unit 122 (step S204). Next, the abnormality diagnosis unit 124 of the control device 100 calculates the increase rate R [%] of the process cycle time (step S206). Here, the process cycle time increase rate R is expressed by the following equation.
R = ((T-Ts) / Ts) * 100

  Next, the abnormality diagnosis unit 124 of the control device 100 determines whether the process cycle time increase rate R is larger than a predetermined threshold A (step S208). If it is determined that the process cycle time increase rate R is equal to or less than the threshold A (NO in S208), the abnormality diagnosis unit 124 determines that no abnormality occurs in the robot 10 (step S210). On the other hand, when it is determined that the process cycle time increase rate R is larger than the threshold A (YES in S208), the abnormality diagnosis unit 124 determines whether the process cycle time increase rate R is smaller than a predetermined threshold B or not. Is determined (step S212). Here, B> A.

  If it is determined that the process cycle time increase rate R is smaller than the threshold B (YES in S212), the abnormality diagnosis unit 124 determines that the robot 10 has a slight abnormality (Step S214). At this time, the warning output unit 126 outputs a mild warning (step S216). For example, the warning output unit 126 may turn on a yellow lamp. On the other hand, when it is determined that the process cycle time increase rate R is equal to or higher than the threshold B (NO in S212), the abnormality diagnosis unit 124 determines that the robot 10 has a serious abnormality (Step S218). At this time, the robot 10 is in an abnormal end state and needs to be promptly repaired. At this time, the warning output unit 126 outputs a heavy warning (step S220). For example, the warning output unit 126 may turn on a red lamp.

  By measuring the process cycle time in the diagnosis target process with high required accuracy, the process cycle time increase rate R can be more reliably increased when an abnormality occurs in the robot 10. Therefore, the control device 100 according to the first embodiment can detect the abnormality of the robot 10 more reliably.

  That is, the measurement values (process cycle time and process cycle time increase rate R) in the process with high required accuracy are more likely to indicate an abnormality when an abnormality occurs in the robot 10 than the measurement in the process with low required accuracy. In other words, in the process with high required accuracy, the measured values (process cycle time and process cycle time increase rate R) are likely to be different between when the robot 10 has an abnormality and when no abnormality has occurred. Therefore, the control device 100 according to the first embodiment can detect the abnormality of the robot 10 more reliably by performing the abnormality diagnosis using the measurement value in the process with high request accuracy.

(Modification)
The present invention is not limited to the above embodiment, and can be appropriately modified without departing from the scope of the present invention. For example, the order of the steps of the flowcharts illustrated in FIGS. 8 to 10 can be changed as appropriate. Also, one or more of the steps of the flowchart may be omitted.

  For example, in FIG. 10, the processes of S210 to S220 may be omitted. And when determination of S208 is YES, you may perform the process which outputs a warning. Also, the process of S202 of FIG. 10 may be performed during the process of S110. That is, measurement of the cycle time may be performed when the process to be diagnosed is performed and the robot 10 is controlled.

  Also, for example, the process of S104 of FIG. 8 may be performed after the process of S110. In this case, since it is set which process is the process to be diagnosed after all the control processes of the robot 10 are completed, it is necessary to measure all process cycle times in each process. On the other hand, as shown in FIG. 8, by setting the diagnosis target process before the control of the robot 10, it is sufficient to measure only the process cycle time related to the diagnosis target process set in advance.

  In the above-described embodiment, the abnormality diagnosis is performed using the cycle time (process cycle time) only in the process with high required accuracy. However, the present invention is not limited to such a configuration. Not only the process with high required accuracy, for example, the cycle time in one or more processes before and after the process may be used to perform abnormality diagnosis. For example, in the example of FIG. 3, the abnormality diagnosis may be performed using the operation time (cycle time) from the start of the process “1” to the end of the process “N”.

  On the other hand, in this case, the cycle time to be measured includes the working time in the process “2” and the process “3” in which the robot 10 operates in cooperation with or in cooperation with other devices (or workers). The working time in the process "2" and the process "3" may be influenced by the work on other devices (or workers). Thereby, even if the cycle time is increased, the increased cause may not be due to the abnormality of the robot 10 to be diagnosed, but may be due to another device (or a worker). Therefore, using the measured value obtained by measuring the cycle time (process cycle time) only in the process with high required accuracy, that is, the time from the end of the process before the process to be diagnosed to the end of the process to be diagnosed. By performing the abnormality diagnosis, it is possible to eliminate the influence of other devices and the like on the measured cycle time. Therefore, it is possible to detect the abnormality of the robot 10 more reliably.

  In the embodiment described above, although the abnormality diagnosis is performed using the process cycle time increase rate R, the present invention is not limited to such a configuration. For example, when the value of T / Ts becomes larger than a predetermined threshold, it may be judged as abnormal.

  In the above-described embodiment, the abnormality diagnosis is performed by measuring the cycle time including the time until the difference between the position of the control target of the robot 10 and the target position falls within the allowable range. It is not limited to such a configuration. For example, the abnormality diagnosis may be performed using the probability that the difference between the position of the control target of the robot 10 and the target position falls within the allowable range within a predetermined time limit. In this case, the probability in the normal robot 10 is higher than the probability in the robot 10 in which an abnormality has occurred. In addition, the tendency is more pronounced in the process with high accuracy requirements. That is, in the process with low requirement accuracy, there is a case where there is not much difference between the probability in the normal robot 10 and the probability in the robot 10 where the abnormality occurs, but in the process with high requirement accuracy, the probability in the normal robot 10 And the probability in the robot 10 in which the abnormality has occurred may be noticeable. That is, the control device 100 in this example also uses the measurement value (probability in the robot 10 that may have an abnormality) and the reference value (probability in the normal robot 10) in the process with high required accuracy. By performing the diagnosis, it is possible to detect the abnormality of the robot 10 more reliably.

  In the above-described embodiment, the abnormality diagnosis is performed using the cycle time (process cycle time). However, the present invention is not limited to such a configuration. As a physical quantity for the process to be diagnosed, an abnormality diagnosis may be performed using not any cycle time but any physical quantity that may fluctuate with the abnormality of the robot 10.

  Further, for example, the abnormality diagnosis may be performed using the arrival deviation amount ΔP shown in FIG. Specifically, assuming that the allowable range in the process to be diagnosed is ± ΔA, the abnormality diagnosis unit 124 calculates the arrival deviation amount increase rate D (= (ΔP / ΔA) * 100) [%]. Then, the abnormality diagnosis unit 124 may determine that an abnormality has occurred in the robot 10 when the arrival deviation amount increase rate D is larger than a predetermined threshold value (reference value). Since the allowable range ΔA is small in the process to be diagnosed, the increase rate D of the arrival deviation amount may be large even if the arrival deviation amount ΔP is small. Then, the arrival deviation amount ΔP can be large when an abnormality occurs in the robot 10. Therefore, even if the arrival deviation amount ΔP is used as the measurement value in the process with the high required accuracy, it is possible to detect the abnormality of the robot 10 more reliably.

  That is, also in this example, when the robot 10 has an abnormality in the measurement values (the arrival deviation amount ΔP and the arrival deviation amount increase rate D) in the step with high required accuracy than the measurement in the step with low required accuracy. It is easy to indicate an abnormality. In other words, in the process with high required accuracy, the measured values (the arrival deviation amount ΔP and the arrival deviation amount increase rate D) are likely to be different between when the robot 10 has an abnormality and when no abnormality has occurred. Therefore, the control device 100 in this example also detects abnormality of the robot 10 more reliably by performing abnormality diagnosis using the measurement value and the reference value (predetermined threshold value) in the process with high required accuracy. Is possible.

  On the other hand, even if a slight abnormality that does not need to be considered occurs in the robot 10, there is a possibility that the reached deviation amount increase rate D may increase. On the other hand, the cycle time (working time) may become longer as the degree of abnormality of the robot 10 becomes larger. Therefore, by performing the abnormality diagnosis using the cycle time, it becomes possible to more surely detect the abnormality of the robot 10.

  Further, in the above-described embodiment, the operation program for performing the abnormality diagnosis uses the program (teaching data) used for the work on the actual actual machine line, but it is not limited to such a configuration. A program for abnormality diagnosis may be separately prepared and abnormality diagnosis may be performed using the program. However, it is not necessary to separately prepare a program for abnormality diagnosis by performing abnormality diagnosis in a process with high required accuracy in a program used for work in an actual actual machine line. If the program used for the actual operation does not include a process with high required accuracy, a process with high required accuracy may be intentionally inserted into the operation program.

  Further, in the embodiment described above, the diagnosis target process setting unit 114 sets only the process “N” having high required accuracy as the diagnosis target process, but the present invention is not limited to such a configuration. The diagnosis target process setting unit 114 may set the diagnosis target process for specifying the start of the cycle time also for the process “N−1” immediately before the process “N”. Thus, by setting the process “N−1” and the process “N” as the diagnosis target process, the working time measurement unit 120 determines the end time of the process “N−1” as the measurement start time of the cycle time It can be easily determined that

  Further, in the embodiment described above, the diagnosis target process setting unit 114 sets only one process “N” with high required accuracy as the diagnosis target process, but the present invention is not limited to such a configuration. When there are a plurality of processes with high required accuracy (processes with accuracy “0”), the diagnosis target process setting unit 114 may set a plurality of processes with high required accuracy as diagnosis target processes. In this case, abnormality diagnosis is performed for a plurality of diagnostic target processes. In this case, a warning may be output when at least one of the plurality of abnormality diagnoses is determined to be abnormal, or a warning may be output when all of the plurality of abnormality diagnoses are determined to be abnormal. . Furthermore, different warnings may be output according to the number of those determined to be abnormal in the plurality of abnormality diagnoses.

  In the embodiment described above, the control device 100 controls the “position” of the control target of the robot 10 (for example, the tip 12 a of the robot 10), and the “target position” is the tip 12 a to be controlled. It is assumed that the position coordinates on the three-dimensional space of are not limited to such a configuration. The control of the “position” of the control target of the robot 10 is not only to control the robot 10 so that the position of the control target of the robot 10 moves to a desired position on the three-dimensional space, but also the position of the control target It may include controlling the robot 10 so that the posture of the part where it is placed becomes the desired posture. Therefore, "position" may include not only position coordinates (x, y, z) in three-dimensional space, but also posture (orientation) (roll, pitch, yaw). Furthermore, the "target position" may include not only desired position coordinates in three-dimensional space, but also desired posture (orientation). Also, in this case, the difference between the target position and the actual position may be considered separately for the difference in position coordinates and the difference in attitude. Then, the control device 100 may control the robot 10 so that both differences fall within the respective allowable ranges.

  Also, in the above-described example, the program can be stored using various types of non-transitory computer readable media and supplied to the computer. Non-transitory computer readable media include tangible storage media of various types. Examples of non-transitory computer readable media are magnetic recording media (eg flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (eg magneto-optical disks), CD-ROM, CD-R, CD-R / W And semiconductor memory (for example, mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, RAM). Also, the programs may be supplied to the computer by various types of transitory computer readable media. Examples of temporary computer readable media include electrical signals, light signals, and electromagnetic waves. The temporary computer readable medium can provide the program to the computer via a wired communication path such as electric wire and optical fiber, or a wireless communication path.

Reference Signs List 1 robot control system, 10 robots, 12a tip, 14 joints, 100 controllers, 112 operation program storage units, 114 diagnosis target process setting units, 116 robot control units, 118 actual position acquisition units, 120 working time measurement units, 122 Measured value management unit, 124 error diagnosis unit, 126 warning output unit, 200 operation program

Claims (4)

An abnormality diagnosis method for diagnosing an abnormality in a robot that operates by driving a joint, wherein the robot is controlled by an operation program configured of a plurality of processes in which predetermined target positions and required accuracy are associated with each other. And
Among the plurality of processes, the process whose requirement accuracy is higher than a predetermined value is set as a process to be diagnosed,
Using the operation program, control is performed so that the difference between the position of the control target of the robot and the target position in the diagnosis target process falls within the allowable range for the required accuracy.
An abnormality diagnosis method of a joint drive robot, which performs abnormality diagnosis of the robot using a measurement value of the process to be diagnosed and a reference value related to the measurement value. Measuring an operation time required for at least one process including the process to be diagnosed;
The abnormality diagnosis method of the joint drive robot according to claim 1, wherein the abnormality diagnosis of the robot is performed using a difference between the measured operation time and a reference value of the operation time. The method according to claim 2, wherein a time from the end of the process before the process to be diagnosed to the end of the process to be diagnosed is measured as the operation time. An abnormality diagnosis apparatus that diagnoses an abnormality of a robot that operates by driving a joint, wherein the robot is controlled by an operation program configured of a plurality of processes in which predetermined target positions and required accuracy are associated with each other. And
Setting means for setting, as a process to be diagnosed, the process whose requirement accuracy is higher than a predetermined value among the plurality of processes;
The process to be diagnosed when control is performed using the operation program such that the difference between the position of the control target of the robot and the target position falls within the allowable range for the required accuracy in the process to be diagnosed An abnormality diagnosis apparatus for a joint drive robot, comprising: a diagnosis value for diagnosing an abnormality of the robot using a measurement value of and a reference value regarding the measurement value.

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